Tou Bao Yan Jiu Yuan·2025-08-25 12:38Core Insights - The report highlights the accelerating shift of value towards upstream applications and service layers in the large model industry, with over 60% of current value concentrated in the infrastructure layer, primarily due to the high costs of AI hardware [6][8][9] - Large models empower applications through three distinct paths: embedded applications, native AI applications, and smart hardware, each with varying levels of commercial maturity [3][18] - The enterprise sector focuses on ROI, while consumer applications show a concentration of traffic towards essential needs, with AI dialogue assistants and search engines capturing over 80% of market traffic [3][18] Industry Overview - The large model industry is structured into four layers: DCF layer, infrastructure layer, model layer, and application layer, with the infrastructure layer currently holding about 66% of the value share [6][8][9] - The application layer is divided into software platforms and hardware carriers, where software platforms can quickly generate revenue due to their lightweight nature, while hardware carriers require significant investment and time to establish [11][14] Application Market Insights - The report categorizes large model applications based on commercial maturity into three paths: mature embedded applications, developing native AI innovations, and nascent smart hardware explorations [18][20] - In the consumer market, AI dialogue assistants dominate, accounting for over 60% of traffic in both global and Chinese markets, while AI search engines also play a significant role [21][24] - The enterprise market primarily utilizes large models for knowledge Q&A, intelligent analysis, decision-making, and customer service, demonstrating significant cost reduction and efficiency improvements [3][18] Competitive Landscape - Key players in the software-driven segment include major cloud service providers and independent development teams focused on vertical applications, each with distinct competitive advantages and challenges [11][12] - Hardware-driven companies aim to integrate large model capabilities with physical devices, facing challenges such as long development cycles and high costs [11][12] - The model layer features participants employing open-source, closed-source, or hybrid strategies to balance ecosystem development and commercial value [12][16] Consumer Application Trends - The global consumer application landscape shows a clear concentration effect, with leading applications like ChatGPT and Microsoft Bing dominating traffic [22][23] - In the Chinese market, local preferences have led to a strong presence of AI dialogue assistants, while independent search forms struggle to gain traction [24][27] - Mobile applications exhibit unique characteristics, with AI dialogue assistants maintaining a leading position, but image editing applications gaining significant market share due to their alignment with mobile usage scenarios [25][26]